Nothing A065
Geekbench ML Score
759
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 12 2024 06:51 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Nothing A065 |
| Model ID | Nothing A065 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 11.00 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
387
72.3 IPS |
|
|
Image Classification (F16)
|
100% |
383
71.7 IPS |
|
|
Image Classification (I8)
|
97% |
675
126.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
485
8.09 IPS |
|
|
Image Segmentation (F16)
|
100% |
493
8.24 IPS |
|
|
Image Segmentation (I8)
|
98% |
559
9.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
959
1.16 IPS |
|
|
Pose Estimation (F16)
|
100% |
921
1.12 IPS |
|
|
Pose Estimation (I8)
|
100% |
3542
4.29 IPS |
|
|
Object Detection (F32)
|
100% |
297
22.1 IPS |
|
|
Object Detection (F16)
|
100% |
287
21.4 IPS |
|
|
Object Detection (I8)
|
61% |
837
62.5 IPS |
|
|
Face Detection (F32)
|
100% |
836
9.94 IPS |
|
|
Face Detection (F16)
|
100% |
843
10.0 IPS |
|
|
Face Detection (I8)
|
86% |
1593
18.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
953
7.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
949
7.36 IPS |
|
|
Depth Estimation (I8)
|
95% |
2067
16.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1783
2.34 IPS |
|
|
Style Transfer (F16)
|
100% |
1731
2.28 IPS |
|
|
Style Transfer (I8)
|
98% |
4330
5.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
496
17.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
495
17.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1514
54.1 IPS |
|
|
Text Classification (F32)
|
100% |
410
588.6 IPS |
|
|
Text Classification (F16)
|
100% |
397
570.0 IPS |
|
|
Text Classification (I8)
|
92% |
283
406.8 IPS |
|
|
Machine Translation (F32)
|
100% |
783
14.4 IPS |
|
|
Machine Translation (F16)
|
100% |
788
14.5 IPS |
|
|
Machine Translation (I8)
|
64% |
296
5.44 IPS |
